Twitter Sentiment Analysis

 I have long dreamt of exploring human behaviour with technology. Thanks to Artificial Intelligence this dream was turned into a reality- I developed an algorithm via which I could conduct Sentiment Analysis using the Twitter API to fetch tweets to act as a dataset. This code required me to read a number of journals and research papers such that the code is succinct and seamless. Following is the code:

from tweepy.streaming import StreamListener
from tweepy import OAuthHandler
from tweepy import Stream
 
import twitter_credentials # Source document name #
class TwitterStreamer():
    def __init__(self):
        pass
    def stream_tweets(self, fetched_tweets_filename, hash_tag_list):
        listener = StdOutListener(fetched_tweets_filename)
        auth =                    OAuthHandler(twitter_credentials.CONSUMER_KEY,twitter_credentials.CONSUMER_SECRET)
        auth.set_access_token(twitter_credentials.ACCESS_TOKEN,twitter_credentials.ACCESS_TOKEN_SECRET)
        stream = Stream(auth, listener)
        stream.filter(track=hash_tag_list)
class StdOutListener(StreamListener):
    def __init__(self, fetched_tweets_filename):
        self.fetched_tweets_filename = fetched_tweets_filename
    def on_data(self, data):
        try:
            print(data)
            with open(self.fetched_tweets_filename, 'a') as tf:
                tf.write(data)
            return True
        except BaseException as e:
            print("Error on_data %s" % str(e))
        return True
          
    def on_error(self, status):
        print(status)
if __name__ == '__main__':
 
    hash_tag_list = ["donal trump", "hillary clinton", "barack obama", "bernie sanders"]
    fetched_tweets_filename = "tweets.txt"
    twitter_streamer = TwitterStreamer()
    twitter_streamer.stream_tweets(fetched_tweets_filename, hash_tag_list)

Hope to conduct more such projects in the future!